Innovative Uses of Electronic Health Records and Social Media for Public Health Surveillance

2014 ◽  
Vol 14 (3) ◽  
Author(s):  
Emma M. Eggleston ◽  
Elissa R. Weitzman
Author(s):  
Michael Klompas ◽  
Michael Murphy ◽  
Julie Lankiewicz ◽  
Jason McVetta ◽  
Ross Lazarus ◽  
...  

2016 ◽  
Vol 38 ◽  
pp. 15-21 ◽  
Author(s):  
A. Kolliakou ◽  
M. Ball ◽  
L. Derczynski ◽  
D. Chandran ◽  
G. Gkotsis ◽  
...  

AbstractBackgroundPublic health monitoring is commonly undertaken in social media but has never been combined with data analysis from electronic health records. This study aimed to investigate the relationship between the emergence of novel psychoactive substances (NPS) in social media and their appearance in a large mental health database.MethodsInsufficient numbers of mentions of other NPS in case records meant that the study focused on mephedrone. Data were extracted on the number of mephedrone (i) references in the clinical record at the South London and Maudsley NHS Trust, London, UK, (ii) mentions in Twitter, (iii) related searches in Google and (iv) visits in Wikipedia. The characteristics of current mephedrone users in the clinical record were also established.ResultsIncreased activity related to mephedrone searches in Google and visits in Wikipedia preceded a peak in mephedrone-related references in the clinical record followed by a spike in the other 3 data sources in early 2010, when mephedrone was assigned a ‘class B’ status. Features of current mephedrone users widely matched those from community studies.ConclusionsCombined analysis of information from social media and data from mental health records may assist public health and clinical surveillance for certain substance-related events of interest. There exists potential for early warning systems for health-care practitioners.


2021 ◽  
Vol 4 (1) ◽  
Author(s):  
James T. H. Teo ◽  
Vlad Dinu ◽  
William Bernal ◽  
Phil Davidson ◽  
Vitaliy Oliynyk ◽  
...  

AbstractAnalyses of search engine and social media feeds have been attempted for infectious disease outbreaks, but have been found to be susceptible to artefactual distortions from health scares or keyword spamming in social media or the public internet. We describe an approach using real-time aggregation of keywords and phrases of freetext from real-time clinician-generated documentation in electronic health records to produce a customisable real-time viral pneumonia signal providing up to 4 days warning for secondary care capacity planning. This low-cost approach is open-source, is locally customisable, is not dependent on any specific electronic health record system and can provide an ensemble of signals if deployed at multiple organisational scales.


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